290 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions at Nature Careers
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materials crystallography research in collaboration with other members of the Iversen group. The candidates must have a PhD in chemistry, crystallography, physics, materials science, nanoscience or similar
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ERC-funded postdoctoral fellow in theoretical developmental biology, using tools from applied mathematics, biophysics, and machine learning A talented and creative researcher is sought to take part
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addition, you will be involved in the implementation and execution of courses and administrative tasks. Your profile PhD in physics experience investigating (nanoscale) magnetic systems at synchrotron
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bioinformatics, and statistical modeling to decode the complex molecular mechanisms that shape human vision. By leveraging high-dimensional data and cutting-edge computational analyses, we aim to uncover
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Ph.D. or equivalent degree in mathematics, physics, computer science, bioinformatics, or a related field Experience in developing deep learning models Ideally, prior experience in analyzing biological
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highly interdisciplinary, integrating big data analysis, state-of-the-art machine learning models, mathematical modeling, and systems biology to elucidate the mechanisms of drug interactions in complex
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research on the topic outlined above is paramount Candidates are expected to be interested in working at the boundaries of several research domains PhD degree in computational biology, bioinformatics
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Qualifications MINIMUM QUALIFICATIONS: PhD (or equivalent) in biology, bioengineering, computer science, physics, or a related field Strong scientific curiosity, motivation, and rigor Strong communication
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SD-25157 RESEARCHER IN ATMOSPHERIC PLASMA TREATMENT OF METALLIC SURFACES FOR INDUSTRIAL APPLICATIONS
occupying more than 5,000 square metres, including innovations in all that we do An environment encouraging curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster
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Lightweight and flexible solar cells Space deployable structures Device analysis in space environments Big data, AI, and machine learning for space solar initiatives Recruitment Attract top-tier postdoctoral